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AI 模型库/zgpu-ai/zlm-v1-iab-domain-classifier-edge
MODEL PROFILE · 模型档案

zlm-v1-iab-domain-classifier-edge

zgpu-ai · zlm-v1-iab-domain-classifier-edge

**The on-device build of `ZeroGPU/zlm-v1-iab-domain-classifier`: a 149M-parameter ModernBERT model that classifies a web destination into IAB content and audience categories from its URL alone, packaged as a 153 MB int8 ONNX file that runs in the browser.** This repository is the exact bundle ZeroGPU serves to edge devices (browsers, Node.js / Docker workers, Android) in production, laid out for transformers.js and onnxruntime. For the full-precision model, the PyTorch checkpoint, the training details and the complete benchmark, see the main repository. - **One output.** `logits` has shape `[batch, 2271]`: the 704 IAB content logits followed by the 1,567 IAB audience logits. Labels in `config.json` carry a head prefix (`content|Sports`, `audience|Interest | Sports | Basketball |`), so a standard text-classification pipeline can run it. - **Per-channel int8 quantization** (QUInt8, dynamic) of the full-precision graph. - **64-token input window**, the length the model was trained with (`max_seq_length` in `postprocess.json`). - **Head-level thresholds:** content 0.60, audience 0.50 (`postprocess.json`).

译文排队中，当前展示来源原文。

文本分析license:apache-2.0
上下文窗口来源未披露
输入 → 输出文本 → 文本
模型权重待核验
档案更新时间2026/10/31 09:42:47
OVERVIEW

模型介绍

**The on-device build of `ZeroGPU/zlm-v1-iab-domain-classifier`: a 149M-parameter ModernBERT model that classifies a web destination into IAB content and audience categories from its URL alone, packaged as a 153 MB int8 ONNX file that runs in the browser.** This repository is the exact bundle ZeroGPU serves to edge devices (browsers, Node.js / Docker workers, Android) in production, laid out for transformers.js and onnxruntime. For the full-precision model, the PyTorch checkpoint, the training details and the complete benchmark, see the main repository. - **One output.** `logits` has shape `[batch, 2271]`: the 704 IAB content logits followed by the 1,567 IAB audience logits. Labels in `config.json` carry a head prefix (`content|Sports`, `audience|Interest | Sports | Basketball |`), so a standard text-classification pipeline can run it. - **Per-channel int8 quantization** (QUInt8, dynamic) of the full-precision graph. - **64-token input window**, the length the model was trained with (`max_seq_length` in `postprocess.json`). - **Head-level thresholds:** content 0.60, audience 0.50 (`postprocess.json`).

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价，请查阅来源渠道。

按月估算基础 Token 费用

—

预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用？

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗？

不是实时结算价格，而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

huggingface · zgpu-ai/zlm-v1-iab-domain-classifier-edge ↗2026/10/31 09:42:47

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。